Abstract MRI has potential to significantly improve breast cancer screening, particularly for women with dense breasts and women who are at higher than average risk for breast cancer. However, improvements in diagnostic accuracy are needed before MRI can be used to screen large numbers of women. The abbreviated MRI scan (AB-MRI) designed by Kuhl and colleagues is a very promising approach to MRI- screening, but relies on a single T1-weighted scan post contrast injection to evaluate enhancement. The lack of information regarding contrast media uptake kinetics may reduce diagnostic accuracy. The research proposed here will test the hypothesis that addition of ultrafast MRI to AB-MRI improves diagnostic accuracy. We propose that AB-MRI combined with ultrafast DCE-MRI can provide effective screening with at a reasonable cost, and with minimal inconvenience for patients. This would result in reliable detection of clinically significant breast cancer years earlier than current screening methods, and thus significantly reduce morbidity and mortality due to breast cancer. A national ECOG-ACRIN clinical trial of AB-MRI screening will begin in late 2016. The basic protocol for this trial is a 10 minute scan with a single post-contrast T1-weighted scan. However, based on results from this lab, the leaders of the ECOG ACRIN trial strongly support inclusion of quantitative ultrafast DCE-MRI in AB-MRI at UChicago (please see the letter of support from the Chair). We propose to: 1. Optimize ultrafast DCE-MRI integrated into AB-MRI with total duration of less than 10 minutes. The ultrafast DCE-MRI scan will have time resolution of less than 3 seconds per image. 2. Develop quantitative analysis of ultrafast data to measure time of initial enhancement (TIE), quantitative Ktrans measurements based on a simplified computational approach, lesion transfer function (LTF) and lesion transit Time(LTT). In addition, we will measure the initial kinetics of lesion enhancement texture. 3. Evaluate the diagnostic accuracy of pharmacokinetic parameters from DCE-MRI. Data will be analyzed in two stages. First, we will use data that is currently being acquired at UChicago to identify the most promising parameters from ultrafast DCE-MRI for further evaluation. Second, we will evaluate the most promising parameters in a ?testing group?. ROC analysis will be used to determine whether parameters from ultrafast imaging can increase the diagnostic accuracy of MRI screening. 4. Compare the diagnostic accuracy of AB-MRI with and without ultrafast DCE-MRI, using both a Reader study and quantitative analysis. New ultrafast DCE-MRI, integrated into AB-MRI scans will significantly reduce morbidity and mortality due to breast cancer, while significantly reducing costs and increasing efficiency.